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Voyage AI Rerank 2.5

First reranker with instruction-following capabilities enabling dynamic query steering and domain-specific optimization. Supports 32K token context (8x Cohere's) through advanced distillation techniques. If you want to compare the best rerankers for your data, try Agentset.

Leaderboard Rank
#4
of 12
ELO Rating
1544
#4
Win Rate
58.0%
#1
Accuracy (nDCG@10)
0.110
#2
Latency
613ms
#6

Model Information

Provider
Voyage AI
License
Proprietary
Price per 1M tokens
$0.050
Release Date
2025-08-11
Model Name
voyage-rerank-2.5
Total Evaluations
3300

Performance Record

Wins1915 (58.0%)
Losses1270 (38.5%)
Ties115 (3.5%)
Wins
Losses
Ties

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Uptime

Performance Overview

ELO ratings by dataset

Voyage AI Rerank 2.5's ELO performance varies across different benchmark datasets, showing its strengths in specific domains.

Voyage AI Rerank 2.5 - ELO by Dataset

Detailed Metrics

Dataset breakdown

Performance metrics across different benchmark datasets, including accuracy and latency percentiles.

DBPedia

ELO 168058.7% WR323W-188L-39T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
583ms
P50 (Median)
613ms
P90
632ms

business reports

ELO 163861.5% WR338W-202L-10T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
612ms
P50 (Median)
521ms
P90
734ms

FiQa

ELO 162767.1% WR369W-167L-14T

Accuracy Metrics

nDCG@5
0.108
nDCG@10
0.119
Recall@5
0.098
Recall@10
0.128

Latency Distribution

Mean
627ms
P50 (Median)
611ms
P90
814ms

arguana

ELO 150859.1% WR325W-221L-4T

Accuracy Metrics

nDCG@5
0.536
nDCG@10
0.543
Recall@5
0.960
Recall@10
0.980

Latency Distribution

Mean
675ms
P50 (Median)
612ms
P90
820ms

MSMARCO

ELO 145146.4% WR255W-247L-48T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
571ms
P50 (Median)
611ms
P90
647ms

PG

ELO 136055.5% WR305W-245L-0T

Accuracy Metrics

nDCG@5
0.000
nDCG@10
0.000
Recall@5
0.000
Recall@10
0.000

Latency Distribution

Mean
612ms
P50 (Median)
612ms
P90
791ms

Build RAG in Minutes, Not Months

Agentset gives you a complete RAG API with top-ranked rerankers and embedding models built in. Upload your data, call the API, and get accurate results from day one.

import { Agentset } from "agentset";

const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");

const results = await ns.search(
  "What is multi-head attention?"
);

for (const result of results) {
  console.log(result.text);
}

Compare Models

See how it stacks up

Compare Voyage AI Rerank 2.5 with other top rerankers to understand the differences in performance, accuracy, and latency.